The transportation industry has long grappled with fragmented systems that slow down operations and frustrate drivers and logistics professionals alike.
Disjointed workflows and confusing interfaces have a direct impact on efficiency, often limiting opportunities for improvement. Many users find themselves juggling 5-10 different products and portals just to complete a few hours of work. This swivel-chair experience is more than a nuisance; it’s a barrier to productivity and workplace satisfaction.
At the heart of a transportation management system (TMS) lies the order. Without orders, there’s no freight to move or tenders to accept. Yet, even with the right tools in place, challenges persist. Sometimes the issue isn’t the software itself, but a misalignment in process. Recognizing this nuance is key to building solutions that actually work for the people using them.
Like every industry, each year brings new and unexpected business challenges. The supply chain is in a constant state of evolution and adaptation, with AI now at the center of both product innovation and product offerings.
Elevating existing offerings to not only improve efficiency but also employee satisfaction is the ultimate mission and AI is helping deliver on this promise. The past 12 months of product development has brought AI deep into the center of existing offerings and now enables the development of customer solutions that were previously impossible.
AI-driven TMS innovation
One example of how to implement AI into a TMS is the integration of an AI agent to assist with tender evaluation and acceptance, helping users sift through hundreds of incoming orders. These tools provide critical insights, evaluating if a lane is profitable, whether capacity exists and if the freight aligns with business goals.
The product innovation sparked by AI is not limited to backend operations. AI and machine learning are being introduced at key decision points to streamline workflows and eliminate redundant tasks, allowing users to focus on higher-value activities. Even the way orders are created is evolving. A simple email can now trigger a new order, with the system extracting relevant data and confirming the transaction automatically.
Meanwhile, the in-cab experience is also being reimagined with safety tools that can notify drivers of hazardous conditions along their route and offer options to reroute or reschedule appointments, all powered by AI.
Efficiency gains and user experience
The results of these innovations are already visible – some companies have reported 50% efficiency gains thanks to automated tender acceptance and reduced manual touchpoints. These improvements also help prevent lost freight due to missed tender timeouts, giving users valuable time back in their day.
Before these updates, users often had to log into their TMS multiple times during off-hours just to ensure tenders were accepted on time. Now, the system handles those tasks automatically.
Next-generation TMS solutions offer a faster, more intuitive experience and onboarding new users has become significantly easier. In some cases, carriers have even been able to navigate the process without any documentation – proof that the user interface is on the right track.
Though little training is required to embrace these new solutions, adoption still hinges on trust. Users need to believe that the technology will make their lives easier. That trust is being built through consistent performance and clear outcomes.
Beyond the bottom line
While AI is often discussed in terms of cost savings and operational efficiency, its impact goes deeper. It helps solve longstanding problems that we have experienced in our daily lives as professionals, upskilling the entire workforce and giving each person tools to become more data-driven and strategic.
As TMS continues to form to the businesses it serves through next-generation technologies like AI and machine learning, the mission remains to improve the efficiency and employee satisfaction of entire supply chains.
